The phenotype of a cancer cell---the set of observable behavioral characteristics including its aggressiveness or pathogenicity, its susceptibility to drug or radiation therapy, its metabolic profile, secreteome, and many other attributes---is not uniquely defined by it's genotype. Rather, it is an emergent property of a complex set of variables that involve chemical and mechanical microenvironmental cues, genetic perturbations, and the epigenetic state of the cell. While great volumes of research have focused on understanding the oncogenic role of each factor individually, compiling them into a holistic picture of cancer growth and progression remains a challenge. SimBioSys, Inc. is developing new computational technologies integrating metabolomic, transcriptomic, and imaging data, in order to construct in silico models of cancer metabolism within realistic spatially- and chemically-heterogeneous microenvironments. At the core of this technology is a novel technique that models the competition for and sharing of metabolites between cells of different types, and/or phenotypes (i.e. stem vs. differentiated, cancerous vs. healthy, etc.). Our intent is to develop a novel computational tool for biomedical researchers that integrates reaction-diffusion and metabolic modeling with large -omics and histology datasets to provide new insight into the behavior of cancers.